Article Review

Social Media Use and Depression and Anxiety Symptoms

The article, “Social media use (SMU) and depression and anxiety symptoms: a cluster analysis” hypothesize that individuals use social media with varying attachments, which may have different mental health outcomes. According to Shensa, Sidani, and Dew (2018), social media use may have negative outcomes such as depression and anxiety. However, the relationship between social media use and the negative health outcomes may be indicative of a more personal experience and not reflective of the volume of SMU. Thus, the study purposes to classify distinct social media use patterns in a sample of young adults, assess the relationship between patterns of SMU and elevated levels of depression and anxiety. Notably, the article is based on a cluster analysis, which means there is no hypothesis. 

The authors conducted the study through an online survey representative of U.S. adults between the ages of 19 to 32. The participants were picked through a non-volunteer platform, and selection of the participants was based on probability. The study covered up to 97 percent of U.S. household and had approximately 55,000 members picked through a non-volunteer platform maintained by Growth for Knowledge. Each participant was provided with a survey that contained at least 140 items although majorities were allowed to answer fewer questions due to skip patterns. The survey took approximately 15 minutes to complete with a token for appreciation in form of $15 for each participant. The study was quantitative and used five variables to identify the various patters of social media use. To test the clustering variables, participants were requested to report the amount of time they spent on social media for personal use. To test on frequency, participants were requested to indicate the frequency with which they visited each of the 11 most popular social network platforms. To test the dependent variables (depression and anxiety), the researchers used the Patient-Reported Outcomes Measurement Information System forms.

The study used multi-collinearity and computed the bivariate correlation matrix as well as the variance inflation factor to examine the five clustering variables. The authors also used a 2-step cluster algorithim and log0likelihood distance measure. To assess the stability of the chosen solution, the study used several techniques including hierarchical method to examine the agglomeration schedule coefficients and random sample to find the final solution. Additionally, the authors used Sata version 14.1, ANOVA, and linear regression to test the results. The final study consisted of 1730 individuals with complete data on the five clustering variables. According to Shensa et al., (2018), the clusters were classified in terms of high on time spent on social media, frequency to measure the number of visits per week, multiple platform use, and problematic use, and social media intensity. The results were categorized under wired and connected clusters, with connected representing high time, frequency, multiple platform use, and SMI with no trace of problematic social media use PSMU. Consequently, wired represented high PSMU, with majority of the participants reporting high time, frequency, multiple platform use, and SMI. The participants that fell under the Wired cluster had a strong correlation with elevated symptoms of depression and anxiety. The group under the Connected Cluster had elevated levels of depression and anxiety but to a lesser degree. 

In conclusion, the authors found greater variations in terms of key SMU characteristics, socio-demographic variations, and relationship with depression and anxiety. Patters of use were more reflective of real-world SMU and had close relationship with depression and anxiety levels. 

The research gave a great deal of compelling data. The findings of the study can be used to develop education and clinical interventions for individuals who are at a high risk of depression and anxiety as a result of social media use. 

References

Shensa, A., Sidani, J. E., Dew, M. A., Escobar-Viera, C. G., & Primack, B. A. (2018). Social media use and depression and anxiety symptoms: A cluster analysis. American Journal of Health Behavior, 42(2), 116-128.